Policy Implications of Stochastic Learning Using a Modified PAGE2002 Model

Stephan Alberth and Chris Hope

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

Abstract: We consider the importance of Endogenous Technical Change (ETC) on the risk profiles for different abatement strategies using the PAGE2002 model with ETC. Three outcomes from this modelling research have significant impacts on the way we ‘optimise’ the greenhouse gas abatement path. Firstly, it was found that for most standard abatement paths there would be an initial "learning investment" required that would substantially reduce the unit costs of CO2 abatement as compared to a business as usual scenario. Secondly, optimising an abatement program where ETC has been included can lead to an increased risk profile during the time of widespread CO2 abatements due to the costs associated with learning. Finally, the inclusion of ETC leads to a slightly deferred optimised abatement path followed by a drastic abatement program that itself would seem highly impractical. Together, the results draw attention to the possibilities of uncovering uncertainty through proactive abatements.

Keywords: Endogenous Technical Change; Optimal Abatement; Climate Change (search for similar items in EconPapers)
JEL-codes: O13 Q55 Q56 (search for similar items in EconPapers)
Pages: 27
Date: 2006-04
New Economics Papers: this item is included in nep-ene
Note: IO
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Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:0633

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